This article presents a general-purpose method for detecting cheating in online courses, which combines anomaly detection and supervised machine learning. Using features that are rooted in psychometrics and learning analytics literature, and capture anomalies in learner behavior and response patterns, we demonstrate that a classifier that is…

Colleges are increasingly turning to predictive analytics to identify "at-risk" students in order to target additional supports. While recent research demonstrates that the types of prediction models in use are reasonably accurate at identifying students who will eventually succeed or not, there are several other considerations for the…

Over the past 20 years, root cause analysis (RCA) has become one of the most widely used retrospective methods for detecting safety hazards in medicine and healthcare. Despite its wide use in management practice and growing popularity in academic research, there is currently a dearth of coverage of RCA in popular healthcare management textbooks…

The National Center for Special Education in Charter Schools (the Center) is deeply committed to ensuring that students with disabilities have equal access to charter schools and that charter schools are designed and operated to enable success for all students. To accomplish this goal, the Center conducts analyses and releases a comprehensive…

Conversations over who should be identified as gifted continue perpetually both within the field and in the popular media. In this article, we focus on the use of local norms as one approach to gifted identification that can increase the equity of advanced educational programs and services while also better achieving their stated purpose of…

Most state departments of education across the United States recommend or require that districts use a home language survey as the first step in a multistep process of identifying students who qualify for English learner student services. School districts typically administer the home language survey to parents and guardians during a student's…

In this article, we propose the concept of "Autonomic Cycle Of Learning Analysis Tasks" (ACOLAT), which defines a set of tasks of learning analysis, whose objective is to improve the learning process. The data analysis has become a fundamental area for the knowledge discovery from data extracted from different sources. In the autonomic…

Although high school graduation rates continue to rise in the United States, reaching 81 percent in the 2012-2013 school year (U.S. Department of Education, 2015), dropout remains a pervasive issue for education systems across the nation. In recent years, Early Warning Systems (EWS), which utilize administrative data to identify students at risk…

Measuring Early Learning Quality & Outcomes (MELQO) was initiated to address needs for child development and quality of early childhood education (ECE) data, specifically for low- and middle-income countries. Drawing from existing tools, MELQO convened a consortium to create open-source tools to be adapted to national contexts, simultaneously…

Learning analytics has reserved its position as an important field in the educational sector. However, the large-scale collection, processing, and analyzing of data has steered the wheel beyond the borders to face an abundance of ethical breaches and constraints. Revealing learners' personal information and attitudes, as well as their activities,…

Learning analytics offers insights into student behaviour and the potential to detect poor performers before they fail exams. If the activity is primarily online (for example computer programming), a wealth of low-level data can be made available that allows unprecedented accuracy in predicting which students will pass or fail. In this paper, we…

This brief is part of a series that explores key implementation considerations. It focuses on the importance of identifying, operationalizing, and implementing the "core components" of evidence-based and evidence-informed interventions that likely are critical to producing positive outcomes. The brief offers a definition of "core components",…

Focused on the use of teacher evaluation data, this case was designed for use in two principal licensure courses, one on data literacy and the other on supervision and personnel. The principal of Baker Middle School has been instructed by the superintendent to use data from the state's new teacher evaluation system to determine which teachers…

School counselors are expected to develop programs that promote academic success for all students, including those at risk for dropping out of school. Knowledge of key indicators of potential dropouts and current trends in dropout prevention research may assist school counselors in better understanding this complex issue. Implementing recommended…

New Visions for Public Schools has leveraged student-level data to help schools identify at-risk students, designed metrics to capture student progress toward graduation, developed data tools and reports that visualize student progress at different levels of aggregation for different audiences, and implemented real-time data systems for educators.…